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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2328/26267
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| Title: | Discovering itemset interactions |
| Authors: | Liang, Ping
Roddick, John Francis
Ceglar, Aaron John
Shillabeer, Anna
de Vries, Denise Bernadette |
| Keywords: | Computing
Data mining
Itemset interaction
Relative support |
| Issue Date: | 2009 |
| Publisher: | Australian Computer Society |
| Citation: | Liang, P., Roddick, J.F., Ceglar, A.J., Shillabeer, A. and de Vries, D.B., 2009. Discovering itemset interactions. ACSC '09: Proceedings of the Thirty-Second Australasian Conference on Computer Science, vol. 91, 133-140. |
| Abstract: | Itemsets, which are treated as intermediate results in association mining, have attracted significant research due to the inherent complexity of their generation. However, there is currently little literature focusing upon the interactions between itemsets, the nature of which may potentially contain valuable information. This paper presents a novel tree-based approach to discovering item-set interactions, a task which cannot be undertaken by current association mining techniques. |
| URI: | http://hdl.handle.net/2328/26267 |
| Appears in Collections: | Computer Science, Engineering and Mathematics - Collected Works
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